Figure 2. The outline of the study
The following chapter leads to theoretical discussion and empiric studies related to the main concepts of this study. It is divided into three sub-chapters: definitions of knowledge, knowledge management strategy and knowledge transfer. The main purpose of each sub-chapter is to open concepts deeply and to demonstrate the theoretical background or the critic linked to the concepts.
1 INTRODUCTION
4 RESEARCH METHODS
5 FINDINGS 6 DISCUSSION 2 CHARACTERISTICS
OF KNOWLEDGE AND THE ROLE OF KNOWLEDGE STRATEGY
3 KNOWLEDGE TRANSFER MECHANISMS ON
MICRO LEVEL
7 CONCLUSIONS
2. CHARACTERISTICS OF KNOWLEDGE AND THE ROLE OF KNOWLEDGE STRATEGY
This chapter reviews the key definitions of knowledge and knowledge transfer strategies which determine a firm´s way to create, share, transfer and store knowledge and thus knowledge transfer mechanisms, as well.
The concepts are defined as knowledge management perspective.
Knowledge management is a multidisciplinary research field, but other sectors are defined inappropriate for this study. Key definitions introduced in this chapter include: knowledge, tacit knowledge, explicit knowledge, stickiness, knowledge strategy and knowledge transfer.
2.1 Definitions of knowledge
The definition of knowledge has been developed over a long period of time. The traditional definition of knowledge is as follows: “justified true belief”. This idea comes from Plato and from other Greek philosophers.
Information is different from mere belief, which is not properly justified, error, which is false, as well as a hypothetical guess, as it lacks the general public approval pursuant to which it is rational to believe (Niiniluoto, 1996). His view of everyday knowledge and scientific knowledge concepts do not necessarily meet the classic definition of knowledge requirements of the truth, even if the truth is, however, like a target of science (Niiniluoto, 1996). It must be remembered, that the ancient Greeks used the data as an example of the geometric information.
This "forever unchanged," a permanent information separates clear perception of the modern world of information.
Knowledge can be defined in many ways based on different perspectives (Alavi & Leidner, 2001). In knowledge management literature the concept of knowledge is related to individuals, tacit knowledge, context and as a dynamic perspective (Spender, 1996b). Edvinsson and Malone´s (1997) divided knowledge in three parts of intellectual capital: 1) human capital
including staff, creativity, technical skills, business capability, customer capability, selling capability, education, motivation etc., 2) structural capital including management, flexibility, renewal capability, service concepts, innovation etc. and 3) relational capital including customers, networks, brands, images and cooperation. This approach focuses on the fact that knowledge is always embedded somewhere and it occurs indirectly as individuals´ competence, organizational structures or human relationships and networks (Edvinsson & Malone, 1997).
Knowledge is commonly distinguished from data, information, knowledge, knowing, intelligence, wisdom and truth (Thierauf, 2001). Data represents objective facts about events and out of special context. Information consists of data within meaningful context or interpretation and it is some kind of form of message. That is why knowledge contains a lot of framed experiences, values, contextual information and insight, which provides a framework for evaluating and incorporating new experiences and information. Knowledge can also be viewed both as a thing to be stored and manipulated and as a process of simultaneously knowing and acting that is applying expertise (Zack, 1999; Blackler, 1995). Figure 3 presents the continuum of understanding by Cleveland (1982), which shows also the implication of context.
Figure 3. Continuum of understanding (Cleveland, 1982)
In organizations, knowledge is embedded in documents or repositories and also in organizational routines, processes, practices, and norms (Argote & Ingram, 2000) and there is a relationship between data, information and knowledge; data is raw numbers and facts, information is processed data, and knowledge is authenticated information. As Nonaka (1994) describes, information is a flow of messages and knowledge consists of the information flow.
In general, knowledge can be seen as understanding, awareness or acquired through study, investigation, observation, or experience over a course of time. It is an individual´s interpretation of information based on personal experiences, skills and competencies (Bollinger & Smith, 2001).
Grayson & O´Dell (1998) define organizational knowledge as what people know about customers, products, processes, mistakes and success. This kind of knowledge is based on databases or through sharing of experiences and best practices. In addition, organizational knowledge accumulates over time.
The character of knowledge can be seen from a dynamic view, too.
According to Nonaka & Takeuchi (1995) knowledge is a dynamic human process of justifying personal belief toward the truth as well as a process of applying expertise, and it is created in social interactions among individuals. Definition of knowledge includes two classifications: explicit knowledge (information) and tacit knowledge (know-how) (Nonaka, 1994).
Explicit knowledge as information implies knowing what something means and it can be written down and codified (Nonaka, 1994). Tacit knowledge as know-how is a practical skill or experience that allows one to do something in an individual way. Tacit knowledge is difficult to formalize and to communicate because it involves cognitive elements (Nonaka, 1994).
The above demonstrates knowledge either as a structural or process approach e.g. objective or functional approach. The structural point of view
focuses on knowledge owned by people and organizations. Nonaka´s (1994) SECI model is a good example of structural approach (the model to create new knowledge by tacit and explicit knowledge and conversion as well, where individual knowledge is transferred to organizational knowledge). On the contrary, Spender (1996b) emphasizes the distinction between individual and social knowledge. It is essential in process approach that knowledge has a special social character e.g. the nature of knowledge is social end embedded in practices.
In order to receive competitive advantage firms have to own capability to create, transfer and share knowledge. Creation of new knowledge can occur when accumulated knowledge is combined with internal innovations or new external knowledge. Many companies have challenges to get balance between exploration (search for new knowledge) or exploitation (existing knowledge resources) (Levinthal & March, 1993).
In summary, Wigg, de Hoog & van der Spek (1997) identify knowledge based on several characteristics which differ from other resources.
According to them knowledge is intangible and difficult to measure, volatile, increases with use, can be used in various process at the same time, often has long lead times, is usually embodied in agents with wills and has wide-ranging impacts on the organization. Figure 4 presents the knowledge typology map; all elements and factors related to knowledge concept based on literature of knowledge management.
Figure 4. Knowledge typology map (Cleveland, 1982)
As mentioned before the definition of knowledge includes two classifications: explicit knowledge (information) and tacit knowledge (know-how) (Nonaka, 1994). In the following sub-chapter the two classifications are presented in detail.
2.1.1 Tacit and explicit knowledge
Knowledge has two types: tacit and explicit (Polanyi, 1962; Hedlund, 1994;
Nonaka & Takeuchi, 1995). Tacit knowledge is difficult to articulate, develops from direct experience, needs face-to-face interaction and shared experience. However, according to Nonaka & Takeuchi (1995) it is possible to assign tacit knowledge to explicit formal via SECI process.
Polanyi (1983) defines both types of knowledge together as interpretation.
Allen (2003) explains Polanyi´s notions unlike other authors; Polanyi´s idea was that human has innate knowledge, cognition and inference capability but, on the contrary, Allen does not agree the idea of interpretation but thinks it is impossible at all to create explicit knowledge via tacit knowledge.
Tacit knowledge is embedded in individual members (Argote & Ingram, 2000) and it includes lessons learned, know-how, judgment, rules of thumb and intuition (Grayson & O´Dell, 1998). Knowledge can also be embedded in an organization´s tools, technology, tasks, relationships and in the various networks formed by combining members, tools and tasks (Argote & Ingram, 2000). Davenport, De Long & Beers (1998) explains by saying:
“Unlike data, knowledge is created invisibly in the human brain (i.e.
tacit), and only the right organizational climate can persuade people to create, reveal, share and use knowledge. Data and information are constantly transferred electronically, but knowledge travels most felicitously through a human network.”
Spender and Grant (1996) stress the paradox of tacit knowledge: because the articulation is so difficult, it may happen that the members in organization don´t understand enough the nature of tacit knowledge. As a result the interpretation can be wrong and cause problems and costs.
In contrast, explicit knowledge is written and formally articulated (Nonaka, 1994). It is also clearly formulated or defined, easily expressed without ambiguity or vagueness, and codified and stored in a database (Bollinger
& Smith, 2001). Even if tacit knowledge is arguably more valuable, explicit knowledge is easy to acquire and can be exploited quickly (Polanyi, 1966) and it is more precisely and formally articulated, although removed from the original context of creation or use (Zack, 1999). According to Polanyi (1983) and Pöyhönen (2004) tacit and explicit knowledge are not opposites but they support each other in building knowledge.
Even there can be difficulties to understand the nature of knowledge, especially tacit knowledge, there is also one factor which related to knowledge. The problem of stickiness, which slows down the transferring of knowledge between sender and recipient, brings more challenges. The following subchapter defines more the phenomenon.
2.1.2 Impact of stickiness
Why is it often difficult to transfer knowledge between and within organizations? Or even if the transfer seems initially to be successful, still any impact on the situation may change rapidly. Szulanski (2003) has recognized so called “sticky” and “stickiness” related to knowledge transfer. Stickiness includes the transfer process and it can be predicted by examining a number of conditions relating to knowledge, sources, context and characteristics of the recipient ((Elwyn, Taubert & Kowalczuk, 2007). Adjective sticky has various synonyms such as immobility, inertness and inimitability. Porter (1994) has used the word inert and Foss et al. (1995) has defined sticky as difficult to imitate. Von Hippel (1994) points out, that stickiness is a function of multiple factors including the nature of knowledge and the choices and attributes of its seekers and providers. The same professional group representatives feel stickiness lower than the representatives from a different approach and that is the reason why in the latter case stickiness is higher and the cost of knowledge transfer will increase.
Not just the knowledge but also the actual transfer could be said to be sticky. Stickiness is an attribute to particular transfer of knowledge which reflects both the characteristics of the transfer situation as well as those of the knowledge being transferred. (Szulanski, 2003.). Szulanski (1996) suggests that problems with stickiness come from language barriers, lack of absorptive capacity, casual ambiguity and problems with the relationship between sender and receiver.
It has already been mentioned that it is important to recognize that transfer is not an act but a process (Szulanski, 1999). The nature of transferring process can be slow, costly and unsuccessful. Many problems occur because knowledge is sticky and difficult to move. Szulanski (2003) noticed that the best practices are so difficult to transfer and many
attempts of transfer fail. Szulanski has described so called knowledge transfer milestones (See figure 5).
MILESTONE
Formation of the Decision to First day of Achievement of
transfer seed transfer use satisfactory performance
Initiation Implementation Ramp up Integration STAGE
Figure 5. The process of knowledge transfer (Szulanski, 1999)
A diachronic analysis of stickiness points out four distinct stages of a transfer: initiation, implementation, ramp-up and integration (Szulanski, 1999):
initiation stickiness is the difficulty to recognize opportunities to transfer and to act upon them to initiate the transfer.
implementation stickiness is recognized as a decision process. The purpose is to begin a recognizable activity between the source and the recipient. Difficulties occur when there are e.g. communication caps between the source and the recipient, or technical caps. Also poor coordination is a difficulty.
ramp-up stickiness occurs when the recipient begins to use acquired knowledge. The main problem will be identifying and resolving unexpected problems that keep the recipient from matching or exceeding a-priori expectations of post transfer performance.
interaction stickiness occur when satisfactory results are initially obtained and the use of new knowledge becomes gradually a routine.
After defining knowledge and illustrating the factors as explicit and tacit knowledge and stickiness related to the concept, there is still reason to collect the wholeness and view its strategic point of view. The following subchapter defines knowledge management strategy which has a significant role in the whole knowledge management perspective.
Knowledge management strategy determines how a firm creates, shares, transfers and stores knowledge, and the strategy affects how to choose right knowledge transfer mechanisms as well.
2.2 Knowledge management strategy
Already Drucker (1968) and Bell (1973) described in due time that the society will in the course of time turn into a “knowledge society”. The predicted evolution has emerged in the 1990s and it is accelerating even more as knowledge-intensive economy expands through global network activity. Knowledge is a critical organizational and strategic resource and a critical factor that provides a sustainable competitive advantage in dynamic economy (Davenport & Prusak, 1998; Foss & Pedersen, 2002;
Grant, 1996a; Hedlund, 1994). Spender (1996) describes knowledge as the most important asset of a company:
“So long as we assume markets are reasonable and the competitive advantage is not wholly the consequence of asymmetric information about those markets, or the stupidity of others, the rent-yielding capabilities must originate within the firm if they are to be the value.”
Before an organization is able to use resources effectively, it must first identify its knowledge management strategy. How do organizations manage knowledge? There are a lot of techniques and technologies to be used. Some organizations capture preferably explicit knowledge and others collect tacit knowledge through the use of expert systems and artificial intelligence (Bollinger & Smith, 2001).
Management strategies can also link into knowledge transfer. According to Jasimuddin (2008) mechanisms which are used for organizational knowledge transfer can be classified into two groups based on the tacit-explicit dichotomy. Focusing on knowledge-as-a-category they can be called as soft and hard mechanisms. Soft mechanisms transfer tacit knowledge through face-to-face interface. Hard mechanisms represent transfer of explicit knowledge using information and communication technology (Jasimuddin, 2008).
The above mentioned view supports Hansen, Nohria & Tierney (1999).
They have divided the knowledge management strategy into two dimensions. According to them some companies automate knowledge management; others rely on their people in sharing knowledge through more traditional means. Authors emphasize that a wrong approach, or trying to pursue both at the same time, can undermine the business.
Many knowledge based firms employ two different knowledge management strategies. In some firms the strategy concentrates on computers. It is called the codification strategy, knowledge is codified and stored in databases where it can be assessed and used easily by anyone in the company (Hansen et al., 1999).
In some firms knowledge is tied to person who develops it and shares it mainly through direct person-to-person contacts. The aim of computers in such companies is to help and support people to communicate knowledge but not to store it. This kind of strategy is called the personalization strategy (Hansen et al., 1999).
According to Hansen et al. (1999) companies, which use knowledge effectively, pursue one strategy predominantly and use another strategy to support the first. The best ratio is 80-20 split: 80 % of knowledge sharing follows one strategy, 20 % the other. Those companies, who try to excel in both strategies risk failing both (Hansen et al., 1999). The company, which
has chosen the codification strategy, can produce to its customer value-added by offering fast, reliability and high quality services to low price. Low cost will improve business efficiency: re-used knowledge reduces costs, save work, reduces communication costs and allows multiple simultaneous projects Hansen et al., 1999).
Person to person based on expertise benefits strategy. It is possible to get higher profits because of high tailoring degree and special expert services.
Company can offer very deep services based on special tacit knowledge (Hansen et al., 1999). Naturally the cost to customer is quite high because of special service.
How to choose the right strategy then? One justification is the nature of product according to Hansen et al. (1999). The codification strategy is justified when the product is a mass product, less tailored or otherwise simple. Simple knowledge is easier to change into information and further codify. High tailoring degree, expertise or complex product need more personal petting and the knowledge is very difficult to change of informational and codify. Foray (2004) presents partly the same criteria as Hansen et al. (1999) and adds the development of company and structural possibilities i.e. both strategies are a possibility to implement.
Scheepers, Venkitachalam & Gibbs (2004) have criticized Hansen´s et al.
(1999) conclusions. Scheepers et al. (2004) suggest that 20/80 strategy combination is not enough but the choice of the strategy should be seen as a “journey”. According to them there is no prevailing strategy journey starting from one point. A company just chooses another strategy and begins to strength it in its organization. Between the main strategies there should be a small but a growing part of another strategy. Scheepers´ et al.
(2004) idea is that the goal of journey is an efficient share of both strategies.
2.2.1 Codification strategy
Codification strategy focuses on connecting people with content through technical networks, developing added value that supports organizing, applying and transferring knowledge. Codification makes the content organized, portable, explicit, and understandable. Codification is the way to save and codify knowledge as databases or user guides, work schedules or benchmark data. Knowledge is codified using a “people-to-documents” approach (Hansen et al., 1999). Conversion from knowledge into information is an essential part of codification (Cowan, 2001). The purpose of codification is to disseminate and develop both “know-how”
and “know why” knowledge in right place and at right time (Hansen et al., 1999). The codification strategy is assumed to be successful for the companies whose business strategy requires re-using existing knowledge (Hansen et al., 1999; Malhotra, 2004). Figure 6 presents a schematic illustration of the knowledge codification process.
Codification strategy is justified when:
Written knowledge products, such as doctrinal manuals, exist.
Similar knowledge is required
The explicit knowledge relates to similar categories and formats Products or services are standardiz
Garavelli, Gorgoglione & Scozzi (2002) have demonstrated the codification process as follows: the holder of knowledge codifies knowledge in various databases using his own cognitive skills. The user of knowledge seeks the knowledge in database and processes the knowledge using his cognitive skills. At this point information in databases has changed into knowledge or is still information. This depends on the user of knowledge and his needs. What is he doing with knowledge and what is the context? If the information is needed to solve new problems, then information has changed into knowledge (Garavelli et al., 2002).
codification interpretation
from knowledge to information from information to knowledge
Figure 6. A schematic representation of knowledge codification process (Garavelli, 2002)
This approach gives a possibility to search for and retrieve codified knowledge without having to contact the developer of knowledge. That gives a possibility to achieve scale in knowledge reuse (Hansen et al., 1999).
2.2.2 Personalization strategy
Personalization strategy focuses on developing social networks, informal teams and communities, to link people with tacit and explicit knowledge.
Tacit knowledge is distributed through managed conversation.
Personalization means providing creative problem solvers – individuals with the tacit knowledge to solve one-off problems means to identify and communicate effectively with other experts (Hansen et al., 1999). The modern technology sets the strategy a new approach. Thus, the purpose of personalization strategy is to use computers just to help people communicate knowledge, not to store it. Technology just helps people to
Personalization means providing creative problem solvers – individuals with the tacit knowledge to solve one-off problems means to identify and communicate effectively with other experts (Hansen et al., 1999). The modern technology sets the strategy a new approach. Thus, the purpose of personalization strategy is to use computers just to help people communicate knowledge, not to store it. Technology just helps people to